How AI is changing the customer experience

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A new survey shows that sales and marketing will be leading areas of AI growth in the three years ahead.

AI-customer-experience

AI customer experience

AI customer experience- AI is rapidly transforming the way that companies interact with their customers. MIT Technology Review Insights’ survey of 1,004 business leaders, “The global AI agenda,” found that customer service is the most active department for AI deployment today. By 2022, it will remain the leading area of AI use in companies (say 73% of respondents), followed by sales and marketing (59%), a part of the business that just a third of surveyed executives had tapped into as of 2019.

Intimacy and efficiency

In recent years, companies have invested in customer service AI primarily to improve efficiency, by decreasing call processing and complaint resolution times. Organizations known as leaders in the customer experience field have also looked toward AI to increase intimacy—to bring a deeper level of customer understanding, drive customization, and create personalized journeys.

Genesys, a software company with solutions for contact centers, voice, chat, and messaging, works with thousands of organizations all over the world. The goal across each one of these 70 billion annual interactions, says CEO Tony Bates, is to “delight someone in the moment and create an end-to-end experience that makes all of us as individuals feel unique.”

Experience is the ultimate differentiator, he says, and one that is leveling the playing field between larger, traditional businesses and new, tech-driven market entrants—product, pricing, and branding levers are ineffective without an experience that feels truly personalized. “Every time I interact with a business, I should feel better after that interaction than I felt before.”

In sales and marketing processes, part of the personalization involves “predictive engagement”—knowing when and how to interact with the customer. This depends on who the customer is, what stage of the buying cycle they are at, what they are buying, and their personal preferences for communication. It also requires intelligence in understanding where the customer is getting stuck and helping them navigate those points.

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Article Credit: MIT Technology Review